Jorge Samper-González
Computer Vision and Pattern Recognition · 2019
A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 36 citations into it
- Artificial Intelligence — 23 citations into it
- Radiology, Nuclear Medicine and Imaging — 14 citations into it
- Physiology — 7 citations into it
- Molecular Biology — 6 citations into it
Whom Jorge Samper-González trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yann LeCun
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- John Ashburner
- Ian J. Goodfellow
- Stephen M. Smith
- Kaiming He
- Karen Simonyan
- Ilya Sutskever
Papers from Jorge Samper-González's perspective
Ordered by how strongly the researchers Jorge Samper-González trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Dropout: a simple way to prevent neural networks from overfitting